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AI Augmented Design: A trend of designing with machine learning – By Aditya Abeysinghe Augmented Intelligence Augmented Intelligence is a subsection of Artificial Intelligence (AI) where AI algorithms are used to obtain information based on an input rather than act autonomously. A system which use AI often replaces human involvement and acts on its own when inputs are provided. AI systems often act independent to humans by making their own actions based on decisions they make. In contrast, augmented intelligence uses data to provide actions that a user could make in the form of information. Therefore, actions based on analysis of data are made by the user as opposed by the system. AI uses different techniques to act based on processed data. Classification, regression, etc. are machine learning types that are used in AI systems to process inputs. Using these types AI can act with or without human input. AI ...

May 28, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AI model building, AI systems, Artificial intelligence, Augmented Intelligence

Data-centric and model-centric machine learning – By Aditya Abeysinghe Different approaches are used in machine learning to build AI (Artificial Intelligence) models. Two common methods used are the model-centric method and the data-centric method. The model-centric method focuses on improving the model and the data-centric method focuses on improving the data used for building the model. Both methods have benefits and drawbacks and both can be used in any model. Model-centric approach In the model-centric approach, the data used for the model is not changed. The model is changed to increase the accuracy and the performance. Different methods to improve the model are used like increasing the training cycles until overfitting, changing values of inputs in each training cycle etc. Most machine learning models are built using this method to improve the model as it is often easy to change the model when compared to changing data. Data-centric approach ...

May 21, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged Artificial intelligence, data consistency, Data evaluation, data-centric method, model building flow, model-centric method

Private 5G: User-controlled networks? – By Aditya Abeysinghe 5th Generation (5G) networks are faster, reliable and are low in latency over 4th Generation (4G) networks. The use of 5G is seen in new technology trends such as real-time data communications between nearby nodes, connected vehicles etc. 5G uses a different network spectrum and uses a different model for communication using base stations which communicate in a more hierarchical method when compared to that of 4G. Private 5G is a new method with user access and security used for private networking. Public vs Private 5G In a public 5G network, the mobile network operator provides access to users, controls priority, and security. Therefore, the user can only use the speed, security, and priority provided by the network. However, in most business cases security and priority of users need to be controlled beyond those provided by the commercial operator. In this case, a ...

May 14, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged 4G and 5G networks, private 5G network, Private 5G: User-controlled networks

Smart AI: Is AI changing smart device usage? – By Aditya Abeysinghe Smart devices are considered smart because they can automate their services. They often communicate using wireless media to provide required functions to users. A smart device can be any device that can process data; from microcontrollers to smart vehicles. Smart devices often lack storage and compute power to process most algorithms which use Artificial Intelligence (AI) methods. However, many algorithms which are used for AI have been optimized such that they can be used in these devices. Where is AI? AI models are used in processes for computation beyond usual application-based processes. Using AI models, different types of AI methods are used to process data. These models are usually lightweight algorithms which can be used within smart devices. Model training and testing are usually carried out on low memory and computation power such that they could ...

May 8, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AI methods, AI models, AI models in smart devices, communication method, Data processing, high compute power, network and hardware devices

AI Ops: Monitoring and Controlling AI – By Aditya Abeysinghe What is AIOps? Artificial Intelligence for IT Operations (AIOps) is a method of using Artificial Intelligence (AI) to improve operations in IT services. Before AIOps, IT operations were managed manually and any outage was solved manually. However, monitoring and management of components is difficult with use of AI in large-scale systems and in a large number of system functionalities. Therefore, automated management is used in AIOps to reduce issues with unavailability and monitor services of a system. Why use AIOps? Digital operations in most services today use several sources of data. Historical, real-time, network-related data etc. are some forms of data used commonly in digital services. With manual management of these services, these data sources need to be analyzed to identify issues and then minimize their impact. With large amount of data generated from these sources, most digital services ...

Apr 30, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AIOps, Artificial Intelligence for IT Operations, Digital operations

Prescriptive maintenance: An AI method to solve faults – By Aditya Abeysinghe Maintenance of systems is a method to avoid issues and make systems up to date and effective. Maintenance is carried out in digital systems using digital components that notify when maintenance is needed and where maintenance is needed. Different methods of maintenance in digital systems are used. AI (Artificial Intelligence) models are used in maintenance methods to predict and suggest when maintenance is required and what needs to be performed to avoid issues. Predictive Maintenance Planned maintenance of a system includes maintenance after a certain milestone or event. For example, maintenance of a machine may be done after a certain period since the last maintenance. This type includes a condition on which a system should be maintained. With this maintenance method, systems are repaired when the event to be maintained is planned even when there is no issue. Therefore, ...

Apr 23, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged Prescriptive Maintenance with AI, Prescriptive maintenance:

Rise of privacy in AI-based computation – By Aditya Abeysinghe AI (Artificial Intelligence) is used in many digital apps regardless of computational and storage capacities of devices. AI is used in devices from small-scale edge devices to large-scale server systems. Growing usages of AI in have caused benefits while also causing several issues. Breach of privacy is one issue in AI that is commonly reported. Ethics when using AI The lifecycle of deploying an AI model composes of gathering data for training, selecting features to build a model, training etc. Ethics in AI are guidelines that need to be followed in each of these stages to ensure AI models and systems are transparent to users. Ethics in AI ensures that there is a set of rules that each member who involves in deploying an AI model should comply with and that there are no hidden benefits that members gain ...

Apr 16, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AI, Artificial intelligence, General Data Protection Regulation

Distributed AI – Could AI processing be faster? By Aditya Abeysinghe Distributed AI (Artificial Intelligence) is a field of AI where data processing is distributed across multiple nodes instead of processing at the source. A common issue with data analysis today is that it is difficult for a central processing source to process massive amounts of data generated by various types of sources. With distributed AI, processing of data is distributed using a system of nodes which can process synchronously and provide analyzed data. Patterns in Distributing AI processes Distributed AI is used in some systems to collect data from edge devices and then analyze it in the cloud by sending data between these devices and the cloud. AI models are trained in the cloud using data received from edge devices and then the output can be sent to the edge. This method of distributing AI processing using the ...

Apr 9, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AI processes, Artificial intelligence, Distributed AI

Software defined storage: A trend for virtualizing data storage? By Aditya Abeysinghe Software defined storage (SDS) is a storage model that separates software used in storage media from the hardware. SDS uses software that controls the hardware and network resources used in data storages. This allows storage to be added or removed without depending on the hardware. The main benefit of this model is flexible storage and maintenance of storage in devices using software. The methodology used Different types of SDSs exist and the methodology used depends usually on the type. A type of SDS is storage virtualization. In this type, a hardware-based storage is used and software is used to virtualize this storage such that it can be used by different processes and monitored centrally. Using virtualization, SDS creates virtual disks which are shown as different storage units within the same hardware storage. This method will also use management ...

Apr 2, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged Application Programming Interfaces, hardware, SDS, Software defined storage, virtualization

AI Governance: Is controlling AI processes useful? By Aditya Abeysinghe Deploying an AI system includes several processes from gathering data to build AI models to testing the system to be deployed. Most businesses which deploy AI systems require a set of policies at each process of this deployment. These policies include which approach to be used, which tools and methods to be used etc. These set of processes, called AI Governance, is used to define how an AI system needs to be deployed while enhancing management of risk, cost, and scope. What is required to achieve AI governance? AI governance of an AI system is regulated by the organizational structure which monitors AI processes from data collection to deployment. The structure may differ from the size of the system, number of teams involved, and the cost and time of completing the AI system. Usually, the structure has members with ...

Mar 26, 2022 Posted by eLanka admin In Aditya Abeysinghe, Articles Tagged AI Governance, AI models, AI system